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DBMS > EJDB vs. Google Cloud Datastore vs. RavenDB vs. Spark SQL

System Properties Comparison EJDB vs. Google Cloud Datastore vs. RavenDB vs. Spark SQL

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Editorial information provided by DB-Engines
NameEJDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonRavenDB  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionEmbeddable document-store database library with JSON representation of queries (in MongoDB style)Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformOpen Source Operational and Transactional Enterprise NoSQL Document DatabaseSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument storeDocument storeDocument storeRelational DBMS
Secondary database modelsGraph DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.31
Rank#296  Overall
#44  Document stores
Score4.36
Rank#72  Overall
#12  Document stores
Score2.84
Rank#101  Overall
#18  Document stores
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitegithub.com/­Softmotions/­ejdbcloud.google.com/­datastoreravendb.netspark.apache.org/­sql
Technical documentationgithub.com/­Softmotions/­ejdb/­blob/­master/­README.mdcloud.google.com/­datastore/­docsravendb.net/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperSoftmotionsGoogleHibernating RhinosApache Software Foundation
Initial release2012200820102014
Current release5.4, July 20223.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoGPLv2commercialOpen Source infoAGPL version 3, commercial license availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCC#Scala
Server operating systemsserver-lesshostedLinux
macOS
Raspberry Pi
Windows
Linux
OS X
Windows
Data schemeschema-freeschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyes infostring, integer, double, bool, date, object_idyes, details herenoyes
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.nono
Secondary indexesnoyesyesno
SQL infoSupport of SQLnoSQL-like query language (GQL)SQL-like query language (RQL)SQL-like DML and DDL statements
APIs and other access methodsin-process shared librarygRPC (using protocol buffers) API
RESTful HTTP/JSON API
.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API
JDBC
ODBC
Supported programming languagesActionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Java
Python
R
Scala
Server-side scripts infoStored proceduresnousing Google App Engineyesno
TriggersnoCallbacks using the Google Apps Engineyesno
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replication using PaxosMulti-source replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflowyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.
Foreign keys infoReferential integrityno infotypically not needed, however similar functionality with collection joins possibleyes infovia ReferenceProperties or Ancestor pathsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID, Cluster-wide transaction availableno
Concurrency infoSupport for concurrent manipulation of datayes infoRead/Write Lockingyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nono
User concepts infoAccess controlnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Authorization levels configured per client per databaseno

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More resources
EJDBGoogle Cloud DatastoreRavenDBSpark SQL
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